UNHCR Chart Generation MCP Server
Enables AI agents to generate UNHCR-styled data visualizations including bar, line, pie, and scatter charts with refugee and population data, returning charts as base64-encoded images.
README
UNHCR Chart Generation MCP Server
This MCP (Model Context Protocol) server in smithery.ai provides tools for generating UNHCR charts using the FastAPI chart generation service. It allows AI agents to create various types of charts (bar, line, pie, etc.) with UNHCR data visualization.
This server interacts with the UNHCR Chart Generation API.
Features
- Generate various types of charts (bar, line, pie, scatter) with UNHCR data
- Create population trend charts for refugee data
- Generate comparison charts with multiple datasets
- Customize chart titles, labels, and styling
- Return charts as base64-encoded images for easy integration
Connect to MCP Server
To access the server, open your web browser and visit the following URL: https://smithery.ai/server/@rvibek/mcp_unhcrpyplot
Configure the MCP host/client as needed.
API Endpoint
The server generates charts using the following API endpoint:
https://unhcrpyplot.rvibek.com.np/plot
The API accepts JSON payloads with the following structure:
{
"chart_type": "string",
"title": "string",
"subtitle": "string",
"x_label": "string",
"y_label": "string",
"data": {
"labels": ["string"],
"values": [number]
}
}
MCP Tools
The server exposes the following tools:
generate_unhcr_graph
Generate a UNHCR chart using the FastAPI chart generation service.
Parameters:
chart_type(required): Type of chart to generate (bar, line, pie, scatter, etc.)title(required): Main title of the chartsubtitle(required): Subtitle describing the chart contentx_label(required): Label for the x-axisy_label(required): Label for the y-axislabels(required): List of labels for the data points (e.g., years, countries)values(required): List of numerical values corresponding to the labels
Returns:
- Dictionary containing the chart image as base64 and metadata
generate_comparison_chart
Generate a comparison chart with multiple datasets.
Parameters:
chart_type(required): Type of chart (bar, line, etc.)title(required): Main title of the chartsubtitle(required): Subtitle describing the chart contentx_label(required): Label for the x-axisy_label(required): Label for the y-axisdatasets(required): List of datasets, each containing 'label', 'labels', and 'values'
Returns:
- Dictionary containing the chart image as base64 and metadata
generate_population_trend_chart
Generate a population trend chart for UNHCR data.
Parameters:
years(required): List of years for the x-axispopulation_counts(required): List of population counts for each yearcountry_name(optional): Name of the country or region being visualized (default: "Country")chart_type(optional): Type of chart (line, bar, etc.) (default: "line")
Returns:
- Dictionary containing the chart image as base64 and metadata
Example Usage
Here's an example of how to use the generate_unhcr_graph tool:
# Generate a bar chart showing refugee population trends
result = generate_unhcr_graph(
chart_type="bar",
title="Nepali Refugees and Asylum Seekers in Canada (2020-2021)",
subtitle="UNHCR Population Data",
x_label="Year",
y_label="Number of People",
labels=["2020", "2021"],
values=[205, 114]
)
Response Format
Successful chart generation returns:
{
"status": "success",
"chart_type": "bar",
"title": "Chart Title",
"image_base64": "base64_encoded_image_string",
"image_format": "png",
"message": "Successfully generated bar chart: Chart Title"
}
License
MIT
Acknowledgments
This project uses the UNHCR Chart Generation API for creating visualizations of UNHCR data.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.